About Business Unit:
The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team of innovative problem solvers develops and builds products that position Epsilon as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full-cycle product engineering and data teams chart the future and set new benchmarks for our products, by using industry standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence. Driven by a passion for delivering smart end-to-end solutions, this team plays a key role in Epsilon’s success story.
We are seeking a Senior Manager to lead the engineering strategy, delivery, and operations for our high-performance Cloud and AI platforms. This role combines people leadership and hands-on technical depth: you will coach and grow a team of engineers, set the technical direction for Agentic AI capabilities, and ensure those systems are securely and reliably delivered on our cloud-native infrastructure. You will partner closely with Product, Data, Security, and Architecture stakeholders to translate business outcomes into a clear roadmap, measurable execution plans, and scalable platform capabilities.
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Engineering Leadership: Lead, coach, and develop a team of engineers; set clear expectations, provide regular feedback, and build a culture of quality, ownership, and continuous improvement.-
Technical Strategy & Architecture: Own platform architecture and standards for AI and cloud services; guide design reviews and ensure solutions are scalable, secure, and maintainable across Python and Java/C# ecosystems.
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AI Platform Ownership: Drive the roadmap and delivery of Enterprise Agentic AI Platforms, including model access patterns, orchestration (e.g., LangGraph), and retrieval systems (e.g., vector databases) on AWS Bedrock.
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Delivery & Execution: Plan and deliver platform outcomes end-to-end—prioritization, staffing, milestones, risks, and dependencies—ensuring predictable delivery and measurable business impact.
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Cloud Reliability & Operations: Ensure reliable production operations on AWS and Kubernetes (EKS); establish on-call practices, incident management, SLOs/SLAs, and post-incident learning to continuously improve resilience.
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Platform Governance & FinOps: Drive governance for infrastructure as code (e.g., Terraform), security controls, cost management, and technical debt reduction across environments and services.
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Stakeholder Partnership: Partner with Product, Data, Security, and business leaders to align platform roadmaps with outcomes; communicate progress, trade-offs, and decisions with clarity.
Required Skills & Qualifications:
Experience: 14+ years in software engineering with 3+ years leading engineering teams (hiring, coaching, performance management) in cloud-native environments.-
People Leadership: Demonstrated ability to build high-performing teams, mentor senior engineers, and establish effective delivery rituals and engineering culture.
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Technical Depth: Strong architectural judgment and hands-on experience across Python and Java (Spring Boot) or C# (.NET), including API design, distributed systems, and integration patterns.
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GenAI Platform Expertise: Proven experience delivering RAG, LLM orchestration, and Agentic AI workflows into production with appropriate evaluation, guardrails, and governance.
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Cloud & DevOps: Deep knowledge of AWS services, Docker, Kubernetes, and Terraform, including CI/CD, observability, security, and reliability practices.
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Data & Platform Systems: Experience with data platforms and stores such as Databricks, SQL, Redis, and vector databases; ability to define platform interfaces and reliability requirements for dependent teams.
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Education: Bachelor’s degree in computer science or a related engineering field (Master’s preferred).
Preferred Attributes:
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Proven track record of scaling AI-enabled platforms from concept to enterprise adoption, including operating model, onboarding, and enablement for partner teams.
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Experience modernizing legacy architectures into event-driven microservices, while maintaining reliability and managing risk in high-availability production systems.
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Strong cross-functional leadership (Product, Data, Security, Architecture) with the ability to influence without authority and drive alignment across multiple teams and priorities.
